Method and System for an Adaptive Auto-Focus Algorithm

Abstract

A method and system for auto-focusing is presented that receives an image at an image capture device, determines a focus measure of the image, and adjusts a focus of the image by moving a lens in the image capture device in a first direction until a maximum focus measure position is reached. The method and system then evaluates a noise level of the focus measure and continues to adjust the focus of the image by further moving the lens in the first direction until the focus measure is decreased by an adaptive threshold amount, wherein the adaptive threshold amount is based on the noise level of the focus measure. The method and system then adjusts the focus of the image by moving the lens in a second direction to the maximum focus measure position.

Description

FIELD OF INVENTION[0001]The invention relates to image processing, and more specifically to automatic focusing of an image based on a noise level of the focus measure.BACKGROUNDRelated Art[0002]Many current digital cameras feature automatic focusing that consists of an optical system with one or more sensors and a control system that positions a lens along an optical axis to automatically detect the best focus. The sensor evaluates the focus measure, typically the sum of the gradients in the image, and stops the lens at the position of the maximum focus measure, which is the position of sharpest focus.[0003]In order to ascertain that the actual sharpest focus position has been found, many digital cameras employ an auto-focus algorithm that includes a process of overshooting the sharpest focus point by continuing to move the lens past the suspect sharpest focus point to create some blurring of the image. If the blurring occurs then the camera assumes that the sharpest focus position ...

AI Technical Summary

Benefits of technology

The patent text describes a system that uses a processor to perform certain tasks. The technical effect of this system is to improve the efficiency and accuracy of processing tasks.

Problems solved by technology

However, doing so may result in an unreliable validation and may result in missing the sharp focus position.

A more cautious auto-focus algorithm may increase the overshoot significantly to ensure validation of the position of sharpest focus but may result in unpleasant blurring being shown to the operator of the camera.

In low light conditions the image and focus measure become obscured with noise in the image thereby prompting a much longer overshoot.

Typical auto-focus algorithms incorporate a pre-defined blurring-overshoot threshold that is designed for a “normal” set of conditions, but is not the most efficient hi high illumination / low noise environments and may not be useable in low illumination / high noise environments.

Such deficiencies result in less than optimum auto-focusing in both high and low focus, measure situations and possibly no ability to auto-focus in low light conditions.

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